Methods and devices for displaying trend and variability in a physiological dataset

Abstract

Embodiments of the invention are directed to methods and devices for displaying trends and variability in a physiological dataset. The method comprises obtaining the physiological dataset, applying a smoothing algorithm to the physiological dataset to obtain a trend of the physiological dataset, applying a variability algorithm to the physiological dataset to obtain the variability of the physiological dataset, outputting a graph of the trend of the physiological dataset, and outputting a graph of the variability of the physiological dataset.

1 . A method of displaying trends and variability in a physiological dataset, comprising, on a processor:
 obtaining the physiological dataset;   applying a smoothing algorithm to the physiological dataset to obtain a trend of the physiological dataset;   applying a variability algorithm to the physiological dataset to obtain the variability of the physiological dataset;   outputting a graph of the trend of the physiological dataset; and   outputting a graph of the variability of the physiological dataset.   
     
     
         2 . The method of  claim 1 , wherein the physiological dataset is based on data obtained from a patient's respiratory system. 
     
     
         3 . The method of  claim 1 , wherein the smoothing algorithm is one of a moving average algorithm and a digital filter algorithm. 
     
     
         4 . The method of  claim 1 , wherein the graph of the trend of the physiological dataset and the graph of the variability of the physiological dataset are one of overlaid and graphed adjacently. 
     
     
         5 . The method of  claim 1 , wherein the graph of the variability of the physiological dataset comprises an envelope bounded on the top by a plot of the maximums identified by the variability algorithm and bounded on the bottom by a plot of the minimums identified by the variability algorithm. 
     
     
         6 . The method of  claim 5 , wherein the space between the bounds is shaded. 
     
     
         7 . The method of  claim 6 , wherein the graph of the variability of the physiological dataset is used to assess and diagnose apnea. 
     
     
         8 . The method of  claim 1 , wherein the physiological dataset is interbreath interval data. 
     
     
         9 . The method of  claim 1 , wherein the graph of variability of the physiological dataset is a function of fractal scaling coefficients calculated at various time points and over various time windows of the dataset. 
     
     
         10 . The method of  claim 1 , wherein the graph of variability of the physiological dataset comprises one or more of, error bars, line graphs, momentum bars, shaded areas under a curve, and a stochastic plot. 
     
     
         11 . The method of  claim 1 , wherein the magnitude of the variability which is displayed by the graph of variability of the physiological dataset is calculated as a function of at least one of, the raw dataset, the smoothed dataset, multiple smoothed datasets, the fractal scaling coefficients of the dataset, or the stochastic coefficients of the dataset. 
     
     
         12 . A device comprising:
 a transthoracic impedance measurement device to obtain a physiological dataset;   a processor receiving the physiological dataset from the measurement device, and adapted to:
 apply a smoothing algorithm to the physiological dataset to obtain a trend of the physiological dataset; and 
 apply a variability algorithm to the physiological dataset to obtain the variability of the physiological dataset ; and 
   an output device coupled to the processor and adapted to:
 output a graph of the trend of the physiological dataset; and 
 output a graph of the variability of the physiological dataset. 
   
     
     
         13 . A system for displaying trends and variability in a physiological dataset, comprising:
 a patient monitoring device;   at least one sensor coupled to the patient monitoring device;   a processor contained within the patient monitoring device and receiving patient data from the at least on sensor;   a screen contained within the patient monitoring device and receiving display information from the processor;   wherein the processor:
 obtains the physiological dataset from the at least one sensor; 
 applies a smoothing algorithm to the physiological dataset to obtain a trend of the physiological dataset; 
 applies a variability algorithm to the physiological dataset to obtain the variability of the physiological dataset; 
 outputs a graph of the trend of the physiological dataset to the screen; and 
 outputs a graph of the variability of the physiological dataset to the screen. 
   
     
     
         14 . The system of  claim 13 , wherein the physiological dataset is based on data obtained from a patient's respiratory system. 
     
     
         15 . The system of  claim 13 , wherein the smoothing algorithm is one of a moving average algorithm and a digital filter algorithm. 
     
     
         16 . The system of  claim 13 , wherein the graph of the trend of the physiological dataset and the graph of the variability of the physiological dataset are one of overlaid and graphed adjacently. 
     
     
         17 . The system of  claim 13 , wherein the graph of the variability of the physiological dataset comprises an envelope bounded on the top by a plot of the maximums identified by the variability algorithm and bounded on the bottom by a plot of the minimums identified by the variability algorithm. 
     
     
         18 . The system of  claim 17 , wherein the space between the bounds is shaded. 
     
     
         19 . The system of  claim 18 , wherein the graph of the variability of the physiological dataset is used to assess and diagnose apnea. 
     
     
         20 . The system of  claim 13 , wherein the physiological dataset is interbreath interval data.